My research focuses on lowering the barrier to performing and evaluating high-quality science. While this may have many possible meanings depending on context or application, I believe it starts with generating reproducible and stable results. I have developed or contributed to a number of projects which have approached this from several different angles, including:
In addition to contributing to these tools, standards, and techniques, I adopt many of them in my own research as well. A series of my publications is linked below, which shows how researchers can go from comparing methods for evaluating the stability of their analysis pipelines, up to ultimately improving the quality of their data-driven predictive models using these techniques.
While there are many more things that could be said or explored, if you're interested in looking a little bit closer at what I do and how I do it, feel free to check out the links below. Everything I do is and will be open, and will likely be more up-to-date than this website if you go directly to the source.